 From Robustness to Privacy and BackInternational Conference on Machine Learning (ICML), 2023 |
 Robustness Implies Privacy in Statistical EstimationSymposium on the Theory of Computing (STOC), 2022 |
 How to Make Your Approximation Algorithm Private: A Black-Box
Differentially-Private Transformation for Tunable Approximation Algorithms of
Functions with Low SensitivityInternational Workshop and International Workshop on Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM), 2022 |
 Algorithms with More Granular Differential Privacy GuaranteesInformation Technology Convergence and Services (ITCS), 2022 |
 On robustness and local differential privacyAnnals of Statistics (Ann. Stat.), 2022 |
